Abstract
Palpable progress in Internet of Things (IoT) and Wireless Sensor Networks (WSN) are quickly turning Industry 4.0 a reality thus having a deep effect on every angle of the manufacturing industry, from logistics to quality control. The measurement for the quality control no longer will be made in a distinct metrology section, but instantaneously on the production line. Smart sensors might be able to register and transmit the recorded data yet no real added-value is obtained from this if the recorded data is not utilized to decide how to improve a process. However, the methods utilized on how to use this is a substantial challenge and it should lead engineers to make the correct decisions. The continuous circulation of information from WSNs to the decision makers and backwards is the foundation of Industry 4.0. Thus, a comprehensive analysis of the effect of Industry 4.0 on quality control is imperative.
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References
Lasi, H., Fettke, P., Kemper, H.-G., Feld, T., Hoffmann, M.: Industry 4.0. Bus. Inf. Syst. Eng. 6, 239–242 (2014)
Salkin, C., Oner, M., Ustundag, A., Cevikcan, E.: A conceptual framework for Industry 4.0. In: Industry 4.0: Managing The Digital Transformation. pp. 3–23. Springer, Cham (2018)
Foidl, H., Felderer, M.: Research challenges of Industry 4.0 for quality management. In: Innovations in Enterprise Information Systems Management and Engineering. pp. 121–137. Springer, Cham (2015)
Chen, B., Wan, J., Shu, L., Li, P., Mukherjee, M., Yin, B.: Smart factory of Industry 4.0: key technologies, application case, and challenges. IEEE Access. 6, 6505–6519 (2018)
Ahuett-Garza, H., Kurfess, T.: A brief discussion on the trends of habilitating technologies for Industry 4.0 and smart manufacturing. Manuf. Lett. (2018)
Müller, J.M., Buliga, O., Voigt, K.-I.: Fortune favors the prepared: how SMEs approach business model innovations in Industry 4.0. Technol. Forecast. Soc. Change. 132, 2–17 (2018)
Mazali, T.: From industry 4.0 to society 4.0, there and back. AI Soc. 1–7 (2017)
Pedone, G., Mezgár, I.: Model similarity evidence and interoperability affinity in cloud-ready Industry 4.0 technologies. Comput. Ind. 100, 278–286 (2018)
Fuchs, A.: Industrial Trucks in the Age of Industry 4.0. ATZoffhighway Worldw. 9, 3–3 (2016)
Ahuett-Garza, H., Kurfess, T.: A brief discussion on the trends of habilitating technologies for Industry 4.0 and smart manufacturing. Manuf. Lett. 15, 60–63 (2018)
Reischauer, G.: Industry 4.0 as policy-driven discourse to institutionalize innovation systems in manufacturing. Technol. Forecast. Soc. Change. 132, 26–33 (2018)
Featherstone, S.: 13—Computer-integrated manufacturing. In: Featherstone, S. (ed.) A Complete Course in Canning and Related Processes (Fourteenth Edition). pp. 269–275. Woodhead Publishing (2015)
Alguliyev, R., Imamverdiyev, Y., Sukhostat, L.: Cyber-physical systems and their security issues. Comput. Ind. 100, 212–223 (2018)
Radziwon, A., Bilberg, A., Bogers, M., Madsen, E.S.: The smart factory: exploring adaptive and flexible manufacturing solutions. Procedia Eng. 69, 1184–1190 (2014)
. Oussous, A., Benjelloun, F.-Z., Ait Lahcen, A., Belfkih, S.: Big Data technologies: A survey. J. King Saud Univ. Comput. Inf. Sci. (2017
Chen, M., Mao, S., Zhang, Y., Leung, V.C.M.: Introduction. In: Big Data. pp. 1–10. Springer, Cham (2014)
Anshari, M., Almunawar, M.N., Lim, S.A., Al-Mudimigh, A.: Customer relationship management and big data enabled: personalization and customization of services. Appl. Comput. Inform. (2018)
Caesarius, L.M., Hohenthal, J.: Searching for big data: how incumbents explore a possible adoption of big data technologies. Scand. J. Manag. 34, 129–140 (2018)
Nimmagadda, S.L., Reiners, T., Wood, L.C.: On big data-guided upstream business research and its knowledge management. J. Bus. Res. 89, 143–158 (2018)
Benghozi, P.-J., Bureau, S., Massit-Folléa, F.: Définir l’internet des objets. In: L’Internet des objets : Quels enjeux pour l’Europe. pp. 15–23. Éditions de la Maison des sciences de l’homme, Paris (2012)
Lanotte, R., Merro, M.: A semantic theory of the internet of things. Inf. Comput. 259, 72–101 (2018)
Kouicem, D.E., Bouabdallah, A., Lakhlef, H.: Internet of things security: a top-down survey. Comput. Netw. 141, 199–221 (2018)
Standardization, I.O.: for: ISO 9001:2015, Fifth Edition: Quality management systems—Requirements. Multiple, Distributed through American National Standards Institute (2015)
Manders, B., de Vries, H.J., Blind, K.: ISO 9001 and product innovation: a literature review and research framework. Technovation. 48–49, 41–55 (2016)
Natarajan, D.: ISO 9001 Quality management systems. Springer International Publishing (2017)
Van den Broeke, M.M., Boute, R.N., Van Mieghem, J.A.: Platform flexibility strategies: R&D investment versus production customization tradeoff. Eur. J. Oper. Res. 270, 475–486 (2018)
Denkena, B., Krüger, M., Schmidt, J.: Condition-based tool management for small batch production. Int. J. Adv. Manuf. Technol. 74, 471–480 (2014)
Liu, C., Wang, H., Fu, X., Xie, D.: Research on Quality Control under Small Batch Production Condition. In: 2010 International Conference on Measuring Technology and Mechatronics Automation. pp. 147–150 (2010)
Kamble, S.S., Gunasekaran, A., Gawankar, S.A.: Sustainable Industry 4.0 framework: a systematic literature review identifying the current trends and future perspectives. Process Saf. Environ. Prot. 117, 408–425 (2018)
Telukdarie, A., Buhulaiga, E.A., Bag, S., Gupta, S., Luo, Z.: Industry 4.0 implementation for multinationals. Process Saf. Environ. Prot. (2018)
Gifford, C.: The MOM Chronicles ISA-95 Best Practice Book 3.0. International Society of Automation, Research Triangle Park, NC (2013)
Meissner, H., Ilsen, R., Aurich, J.C.: Analysis of control architectures in the context of Industry 4.0. Procedia CIRP. 62, 165–169 (2017)
Godina, R., Matias, J.C.O.: Improvement of the statistical process control through an enhanced test of normality. In: 2018 7th International Conference on Industrial Technology and Management (ICITM). pp. 17–21 (2018)
Li, P., Jiang, P.: Research on quality-oriented outsourcing decision architecture for small-batch parts of multistage machining processes. In: Proceedings of the 22nd International Conference on Industrial Engineering and Engineering Management 2015. pp. 427–433. Atlantis Press, Paris (2016)
Mayr, A., Weigelt, M., Kühl, A., Grimm, S., Erll, A., Potzel, M., Franke, J.: Lean 4.0-A conceptual conjunction of lean management and Industry 4.0. Procedia CIRP. 72, 622–628 (2018)
Vaidya, S., Ambad, P., Bhosle, S.: Industry 4.0—a glimpse. Procedia Manuf. 20, 233–238 (2018)
Merino, J., Caballero, I., Rivas, B., Serrano, M., Piattini, M.: A data quality in use model for Big Data. Future Gener. Comput. Syst. 63, 123–130 (2016)
Sung, T.K.: Industry 4.0: A Korea perspective. Technol. Forecast. Soc. Change. 132, 40–45 (2018)
Bagheri, B., Yang, S., Kao, H.-A., Lee, J.: Cyber-physical systems architecture for self-aware machines in Industry 4.0 Environment. IFAC-Pap. 48, 1622–1627 (2015)
Simons, S., Abé, P., Neser, S.: Learning in the AutFab—The Fully Automated Industrie 4.0 Learning factory of the University of Applied Sciences Darmstadt. Procedia Manuf. 9, 81–88 (2017)
Schuh, G., Potente, T., Wesch-Potente, C., Weber, A.R., Prote, J.-P.: Collaboration Mechanisms to Increase Productivity in the Context of Industrie 4.0. Procedia CIRP. 19, 51–56 (2014)
Sittón, I., Rodríguez, S.: Pattern extraction for the design of predictive models in Industry 4.0. In: Trends in Cyber-Physical Multi-Agent Systems. The PAAMS Collection—15th International Conference, PAAMS 2017. pp. 258–261. Springer, Cham (2017)
Gewohn, M., Beyerer, J., Usländer, T., Sutschet, G.: A quality visualization model for the evaluation and control of quality in vehicle assembly. In: 2018 7th International Conference on Industrial Technology and Management (ICITM). pp. 1–10 (2018)
Acknowledgements
This work was financially supported by the research unit on Governance, Competitiveness and Public Policy (project POCI-01-0145-FEDER-006939), funded by FEDER funds through COMPETE2020—POCI and by national funds through FCT—Fundação para a Ciência e a Tecnologia. Radu Godina would like to acknowledge financial support from Fundação para a Ciência e Tecnologia (UID/EMS/00667/2019).
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Godina, R., Matias, J.C.O. (2019). Quality Control in the Context of Industry 4.0. In: Reis, J., Pinelas, S., Melão, N. (eds) Industrial Engineering and Operations Management II. IJCIEOM 2018. Springer Proceedings in Mathematics & Statistics, vol 281. Springer, Cham. https://doi.org/10.1007/978-3-030-14973-4_17
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